arXiv subjects

Naoki Ito

Publications and source records attributed to Naoki Ito.

10 recordsLinked to original sources

arXiv2026

Charge-Transfer Electronic Structure of NiX$_2$ (X = S, Se)

We investigate the electronic structures of NiS$_2$ and NiSe$_2$ using density functional theory combined with dynamical mean-field theory (DFT+DMFT). A realistic electronic structure within DFT+DMFT was determined by optimizing the double-counting correction to reproduce experimental valence-band photoemission spectra. The validity of the present model is further confirmed by its successful description of the Ni 2$p$ core-level photoemission and Ni $L$-edge x-ray absorption spectra of NiS$_2$. Our results reveal a smaller charge-transfer energy than previously assumed, resulting in substantial ligand-to-Ni charge transfer and a reduced Ni local moment. We clarify how the relative position and interaction between the Ni upper Hubbard band and the antibonding chalcogen-dimer states shape the evolution of the low-energy electronic structure across the NiS$_{2-x}$Se$_x$ series.

cond-mat.mtrl-sci↗

arXiv2026

Probing La-based nickelates with Ni 1$s$ core-level photoelectron spectroscopy

We present a comparative Ni core level photoemission study of La$_3$Ni$_2$O$_7$, Nd$_3$Ni$_2$O$_7$, and LaNiO$_3$ using both the Ni $2p$ and the Ni $1s$. We address the challenges in analyzing the widely investigated Ni $2p$ spectra arising from the substantial overlap in energy of the Ni $2p$ with the La $3d$. We show that on the other hand the deep Ni $1s$ core level does provide a clean view on the intrinsic electronic excitations and we highlight its potential to resolve detailed differences in the electronic structure within the strongly correlated Ruddlesden-Popper series La$_{n+1}$Ni$_n$O$_{3n+1}$.

cond-mat.str-el↗

arXiv2026

UCd$_{11}$: A strongly localized 5$f^3$ material

UCd$_{11}$ is an antiferromagnetic uranium intermetallic compound ($T_{\rm N}$ = 5.3K) with enhanced electron mass and uranium-uranium spacings nearly twice the Hill limit, suggesting a weakly hybridized 5$f$ electronic character. Various x-ray spectroscopy techniques indicate that uranium in UCd$_{11}$ adopts the formal U$^{3+}$ 5$f^3$ configuration, while core-level photoemission spectroscopy (PES) data of UCd$_{11}$ reveal only a weak satellite feature, typically interpreted as a signature of itinerancy. In this work, we present density functional theory (DFT) combined with dynamical mean-field theory (DMFT) calculations of UCd$_{11}$, using material-specific parameters tuned to reproduce valence-band PES spectra at different photon energies, thereby exploiting the energy dependence of photoionization cross sections. Our results demonstrate that UCd$_{11}$ is a highly localized uranium 5$f^3$ system. Furthermore, core-level spectra obtained from a DFT+DMFT Anderson impurity model reveal that, contrary to common assumptions, the presence or absence of satellite structures is not a reliable indicator of strong correlations or itinerant 5$f$ behavior.

cond-mat.str-el↗

arXiv2025

A Study on the Algorithm and Implementation of SDPT3

This technical report presents a comprehensive study of SDPT3, a widely used open-source MATLAB solver for semidefinite-quadratic-linear programming, which is based on the interior-point method. It includes a self-contained and consistent description of the algorithm, with mathematical notation carefully aligned with the implementation. The aim is to offer a clear and structured reference for researchers and developers seeking to understand or build upon the implementation of SDPT3.

math.OC↗

arXiv2025

UTe$_2$: a narrow band superconductor

We investigate the nature of the 5$f$ electrons in the unconventional odd-parity superconductor UTe$_2$, focusing on the degree of covalency, localization versus itinerancy, and dominant electronic configuration. This is achieved using density functional theory (DFT) in combination with dynamical mean-field theory (DMFT) calculations. A key aspect of our approach is the material-specific tuning of the double-counting correction parameter, $\mu_{\rm dc}$, within the DFT+DMFT part. This tuning is guided by the energy dependence of photo-ionization cross-sections in valence band photoelectron spectroscopy. The reliability of the parameters is confirmed by the accurate reproduction of the angle-resolved valence-band photoemission spectra and the U 4$f$ core-level data. The DFT+DMFT model reveals that in UTe$_2$ U 5$f^n$ configurations with n=1 to 4 contribute to the ground state, with the 5$f^2$ configuration being most prevalent and an average 5$f$ shell fillings close to 2.5. The model further suggests that the 5$f$ electrons form narrow bands and that charge fluctuations due to degeneracy play a role in addition to coherent valence dynamics arising from hybridization with the conduction bath. Additionally, the significance of the U 6$d$ states in UTe$_2$ is discussed.

cond-mat.str-el↗

arXiv2022

Gaussian Process Classification Bandits

Classification bandits are multi-armed bandit problems whose task is to classify a given set of arms into either positive or negative class depending on whether the rate of the arms with the expected reward of at least h is not less than w for given thresholds h and w. We study a special classification bandit problem in which arms correspond to points x in d-dimensional real space with expected rewards f(x) which are generated according to a Gaussian process prior. We develop a framework algorithm for the problem using various arm selection policies and propose policies called FCB and FTSV. We show a smaller sample complexity upper bound for FCB than that for the existing algorithm of the level set estimation, in which whether f(x) is at least h or not must be decided for every arm's x. Arm selection policies depending on an estimated rate of arms with rewards of at least h are also proposed and shown to improve empirical sample complexity. According to our experimental results, the rate-estimation versions of FCB and FTSV, together with that of the popular active learning policy that selects the point with the maximum variance, outperform other policies for synthetic functions, and the version of FTSV is also the best performer for our real-world dataset.

cs.LG↗

arXiv2022

Non-learning Stereo-aided Depth Completion under Mis-projection via Selective Stereo Matching

We propose a non-learning depth completion method for a sparse depth map captured using a light detection and ranging (LiDAR) sensor guided by a pair of stereo images. Generally, conventional stereo-aided depth completion methods have two limiations. (i) They assume the given sparse depth map is accurately aligned to the input image, whereas the alignment is difficult to achieve in practice. (ii) They have limited accuracy in the long range because the depth is estimated by pixel disparity. To solve the abovementioned limitations, we propose selective stereo matching (SSM) that searches the most appropriate depth value for each image pixel from its neighborly projected LiDAR points based on an energy minimization framework. This depth selection approach can handle any type of mis-projection. Moreover, SSM has an advantage in terms of long-range depth accuracy because it directly uses the LiDAR measurement rather than the depth acquired from the stereo. SSM is a discrete process; thus, we apply variational smoothing with binary anisotropic diffusion tensor (B-ADT) to generate a continuous depth map while preserving depth discontinuity across object boundaries. Experimentally, compared with the previous state-of-the-art stereo-aided depth completion, the proposed method reduced the mean absolute error (MAE) of the depth estimation to 0.65 times and demonstrated approximately twice more accurate estimation in the long range. Moreover, under various LiDAR-camera calibration errors, the proposed method reduced the depth estimation MAE to 0.34-0.93 times from previous depth completion methods.

cs.CV↗

arXiv2021

Solving Challenging Large Scale QAPs

We report our progress on the project for solving larger scale quadratic assignment problems (QAPs). Our main approach to solve large scale NP-hard combinatorial optimization problems such as QAPs is a parallel branch-and-bound method efficiently implemented on a powerful computer system using the Ubiquity Generator (UG) framework that can utilize more than 100,000 cores. Lower bounding procedures incorporated in the branch-and-bound method play a crucial role in solving the problems. For a strong lower bounding procedure, we employ the Lagrangian doubly nonnegative (DNN) relaxation and the Newton-bracketing method developed by the authors' group. In this report, we describe some basic tools used in the project including the lower bounding procedure and branching rules, and present some preliminary numerical results. Our next target problem is QAPs with dimension at least 50, as we have succeeded to solve tai30a and sko42 from QAPLIB for the first time.

math.OC↗

arXiv2018

BBCPOP: A Sparse Doubly Nonnegative Relaxation of Polynomial Optimization Problems with Binary, Box and Complementarity Constraints

The software package BBCPOP is a MATLAB implementation of a hierarchy of sparse doubly nonnegative (DNN) relaxations of a class of polynomial optimization (minimization) problems (POPs) with binary, box and complementarity (BBC) constraints. Given a POP in the class and a relaxation order, BBCPOP constructs a simple conic optimization problem (COP), which serves as a DNN relaxation of the POP, and then solves the COP by applying the bisection and projection (BP) method. The COP is expressed with a linear objective function and constraints described as a single hyperplane and two cones, which are the Cartesian product of positive semidefinite cones and a polyhedral cone induced from the BBC constraints. BBCPOP aims to compute a tight lower bound for the optimal value of a large-scale POP in the class that is beyond the comfort zone of existing software packages. The robustness, reliability and efficiency of BBCPOP are demonstrated in comparison to the state-of-the-art software SDP package SDPNAL+ on randomly generated sparse POPs of degree 2 and 3 with up to a few thousands variables, and ones of degree 4, 5, 6. and 8 with up to a few hundred variables. Comparison with other BBC POPs that arise from combinatorial optimization problems such as quadratic assignment problems are also reported. The software package BBCPOP is available at https://sites.google.com/site/bbcpop1/.

math.OC↗

arXiv2013

A New Dynamic Pricing Model based on Convex Hull Pricing

This paper presents a new dynamic pricing model (a.k.a. real-time pricing) that reflects startup costs of generators. Dynamic pricing, which is a method to control demand by pricing electricity at hourly (or more often) intervals, has been studied by many researchers. They assume that the cost functions of suppliers are convex, although they may be nonconvex because of the startup costs of generators in practice. We provide a dynamic pricing model that takes into account such cost functions within the settings of unit commitment problems (UCPs). Our model gives convex hull price (CHP), which has not been used in the context of dynamic pricing, though it is known that the CHP minimizes the uplift payment which is disadvantageous to suppliers for a given demand. In addition, we apply an iterative algorithm based on the subgradient method to solve our model. Numerical experiments show the efficiency of our model on reducing uplift payments. The prices determined by our algorithm give sufficiently small uplift payments in a realistic computational time.

math.OC↗